AI powered CX. Disruptor of the status quo? The next step in evolution? Threat? Opportunity? Tool? Weapon?
In 2023 AI has well and truly jumped from the realm of science fiction into our daily lives.
A report by Accenture identified a small group of high performing organisations who have utilised AI to generate 50% more revenue growth and out perform on customer experience (CX) and environmental, Social and Governance Metrics.
A NewVantage Partners survey also found that 99% of fortune 1000 companies are actively investing in AI.
AI clearly has huge potential to improve customer experience and boost user engagement, retention and conversions.
But how will it achieve this?
In this article we will take you through the ins and outs of AI and its role in the future of CX strategy.
We will cover;
So lets jump into it.
What is an AI powered Customer Experience?
When we say Artificial Intelligence we are generally referring to a process called machine learning (ML).
Who better to explain Machine Learning than arguably the most famous AI at the moment, ChatGPT.
I asked ChatGPT to explain machine learning like I’m twelve. Here are the results.
Machine learning is a way for computers to learn how to do things without being explicitly programmed how to do them. Imagine you have a game where you have to guess what number someone is thinking of, and every time you guess, they tell you if you’re too high or too low. After a few tries, you might start to figure out what the number is just by their responses.
This is similar to how a machine learning algorithm works. It is given a set of data and a goal, and it tries different approaches to achieve that goal, learning from its mistakes and getting better over time.
This makes machine learning extremely useful for creating personalised customer experience. By feeding the user’s data into an algorithm the AI is then able to predict the customer’s behaviour. Sounds a little bit creepy right?
With an AI powered CX, an algorithm could recommend products which match the user’s specific tastes. Or remind users to re-order a product when it predicts they will run out.
What does an AI powered customer journey look like?
Imagine, Megan has found the perfect moisturiser that is just right for her skin.
On her morning train commute she gets an email which informs her that it might be time to re-order as her current supply could run out in about a week.
She decides to visit the company’s mobile website. The website recognises her previous order and displays an easy button for her to order with just one click. At the same time the algorithm recommends a serum which other customers often pair with Megan’s favourite moisturiser. With a few more clicks her products are on their way.
By tracking Megan’s order frequency and analysing the behaviour of other customers, the Skincare company created a personalised experience which felt effortless. And Megan’s face stays nice and hydrated.
5 ways AI will help companies to improve their Customer Experience
1. AI helps content to become deeply customised
Customers desire a personalised and contextualised experience.
According to the 2022 Gartner Customer Service and Support Survey, 71% of B2C and 86% of B2B customers expect companies to be well informed about their personal information during an interaction.
The analysis of user data through machine learning can deliver better personalised content such as ;
- Product Recommendations
- Relevant written, audio, or video content suggestions. (Think the Netflix or Youtube Algorithm)
- Marketing emails which target customer specific needs.
Being able to target your audience with product recommendations they are genuinely interested in right when they are in the mindset to make a purchase is an invaluable way to begin the purchasing journey.
2. Ai Chatbots can Pre-Qualify leads to boost conversion
If you are introducing a new product, AI chatbots can help you to build trust in the product.
A pre programed chatbot can answer customer questions about the product through an AI assisted q&A process. This can help you qualify leads without needing to activate your sales team.
As the Chatbot fields questions it can help you to determine whether the product is the right fit for this customer before sending the customer to sales. Saving your team valuable time.
3. AI can help you to predict customer needs
By assessing things like past purchases and behaviors, AI can help predict what items a customer might be interested in or tell them when it’s time to reorder.
Streaming services can suggest movies and TV shows to watch or new music and podcasts to listen to.
This type of AI technology is called Predictive Personalisation. It is widely adopted by many well known brands.
4. Workflows Become More Streamlined
Customer service problems can be easily served through AI without human intervention.
An AI chatbot can field common questions and direct users to the right resource to assist their enquiry. This leaves the customer service team with the time to deal customer needs which require deeper focus.
5. AI improves Customer Retention Efforts
You can identify your company’s pain points by analysing customer behaviour which leads to customers dropping off from your product or service.
With the use of AI you will be able to pinpoint these moments based on real data. Allowing you to address these issues with more accuracy and craft the right solution.
Real world AI powered CX
Volvo – Predicting Breakdowns with Machine Learning.
Swedish Auto Manufacturer Volvo continues to live up to its commitment to safety. It aims to minimise the impact of mechanical and system failures through machine learning.
The Early Warning System analyses millions of events within the car, along with part warranty data and vehicle telemetry to predict which parts of the car may breakdown or fail. Allowing the customer to avoid a catastrophic or inconvenient event by preemptively servicing the part.
ASOS – Steal their look with Ai
The British online clothing retailer took a clever approach to people wanting to emulate outfits which which they have been inspired by.
Users can upload a photo or screenshot to the ASOS app which will then search its database to find clothes which match those in the image.
It’s a great way to find a more affordable alternative to expensive designer styles.
Walgreens – Using purchase Data to track the flu.
The US based pharmacy chain analyses customer purchase data to predict the intensity of the flu and help people take action to keep themselves and their families healthy.
Walgreens use data on the number of anti-viral prescriptions it fills from over 8000 stores. Using this data they can track the spread of the flu.
Customers can view an online map which tells them how bad the flu is in their area while also allowing the company to stock more flu related products in affected regions.
Uniqlo – Clothing recommendations based on your mood.
In select stores, Uniqlo has installed Umood Kiosks which match customers to clothing recommendations subconsciously.
Customers are shown a variety of clothing and colour options and their reaction is analysed through neurotransmitters. Based on their reactions the kiosk then recommends products.
Customers can find a style they’ll love without even pushing a button or saying a word. Truly reaching minority report levels of predictive technology.
KFC – Facial Recognition Chicken
Finishing our list with the strangest and most dystopian option yet. KFC collaborated with Chinese Search Engine Baidu to use facial recognition to predict what a customer will want to eat.
The Algorithm takes into account time of day, the estimated age of the person, gender and their mood to offer them the perfect recommendation.
The system will also remember what you ate to improve it’s recommendation for next time.
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